Mark rate exploration

Author

Norah Brown

Published

August 29, 2024

Methods

  • We pulled raw recreational catch data from CREST database: data sources include creel, iREC, lodge and log-book data. Data is typically in number of marked and unmarked fish kept and released.
  • Filtered the creel data based on high quality creel which meet the following criteria in a given PFMA and month:
    • At least 3 flights for each type of day (weekday or weekend)
    • At least 25 interviews mid week OR at least 10% of interviews from mid-week
    • At least 25 interviews on weekends OR at least 10% of interviews from weekend
    • At least 15 day spread in flights
    • At least 15 day spread in interviews
  • We calculated mark rate for each data source based on number of marked and unmarked fish encountered. We created a cut-off of data for n=100 fish in a given month. If the sample was less than that then there wasn’t enough data to create a mark-rate estimate.

  • Then we calculated an average of mark rate for the five year 2019-2023 period and one for the five year 2014-2018 period for each source.

  • After the averages were calculated, we combined data sources using the following rule:

    • In months 5-9 use creel+ lodge if that data exists, otherwise use iREC

    • In months outside of 5-9 use iREC

  • We included commercial troll data but this did not fill out the data frame any more than using only creel and iREC

Results

Heat Map

iREC & creel data combined 2019-current by catch region

  • Pink borders indicate the estimate includes data from iREC, without the border is creel-only information

Heatmap for mark rate in different catch regions organized by month of the year.

Figure 1: Mark rate heatmap by management area and month. Mark rate is an average of mark rates from 2019-2023.

iREC & creel data combined 2019-current

  • Pink borders indicate the estimate includes data from iREC, without the border is creel-only information

Heatmap for mark rate in different PFMAs organized by month of the year.

Figure 2: Mark rate heatmap by management area and month. Mark rate is an average of mark rates from 2019-2023.

iREC & creel data combined 2014-2018

Heatmap for mark rate in different PFMAs organized by month of the year.Using data from 2014-2018.

Figure 3: Mark rate heatmap by management area and month. Mark rate is an average of mark rates from 2014-2018.

iREC & creel data combined 2014-2018 Catch region

Heatmap for mark rate in different PFMAs organized by month of the year.Using data from 2014-2018.

Figure 4: Mark rate heatmap by management area and month. Mark rate is an average of mark rates from 2014-2018.

Individual data sets

Datasets for 2019-2023 separated out by source.

(a) iREC data only

(b) creel data only

(c) logbook data only

(d) troll data only

(e) biodata only

Figure 5: Mark rate heatmap by management area and month. Mark rate is an average of mark rates from 2019-2023.Mark rate is separated by data source.

Plots over time

Re-created these using the “best practices” combo of creel and irec

Georgia Strait Central

Georgia Strait South

Johnstone Strait South

Juan de Fuca Sport

West Coast Vancouver Is Sport

Area 11

Area 111

Area 12

Area 13

Area 14

Area 15

Area 16

Area 17

Area 18

Area 19 GS

Area 19 JDF

Area 20

Area 20 East

Area 20 West

Area 21

Area 121

Area 23 (Alberni Canal)

Area 23 (Barkley)

Area 123

Area 24

Area 124

Area 25

Area 125

Area 26

Area 126

Area 27

Area 127

Area 28

Area 29